Repository files navigation

cop

Some custom reduction operations for data distributed over MPI.

Installation

The development version is maintained on GitHub. Because the package uses git submodules, you can not use any of the install_github() functions. Instead you can do this:

source("https://gist.githubusercontent.com/wrathematics/ccf6bf366279e099563e69e56b4fde59/raw/6daf038ca56f4f531f631f80a54d8d9aa70b4bbb/ighwsm.r")
ighwsm("RBigData/cop")

API

Dense, numeric matrix reductions:

MethodExplanation
cop_allreduce()Reduction that accepts a custom operation (R function). The function has some strong caveats; see ?cop::cop_allreduce for details.
cop_reduce()
qr_allreduce()Reduction where each process owns the R matrix of a QR decomposition, and the reduction is (conceptually) op = function(a, b) qr.R(qr(a, b)).
qr_reduce()

Sparse matrix reductions:

MethodExplanation
spadd_allreduce()Reduction where each process owns a sparse matrix (dgCMatrix from the Matrix package), and the reduction sums all of the matrices.
spadd_reduce()

The difference between the _reduce() and the _allreduce() variants is that with the former, only the process specified by the root argument receives the return.

The package also has some helper utilities:

MethodExplanation
mpi_cat()Helper cat() function.
mpi_print()Helper print() function.

These are similar to pbdMPI::comm.cat() and pbdMPI::comm.print(), although here printing is guaranteed to occur in rank order.

Examples

For the sake of example, we can build a matrix addition custom reducer:

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
add=function(a, b) a+bout= cop_allreduce(x, op=add, commutative=TRUE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(add)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

Most of this is just printing and boilerplate, but even so it's still pretty simple. If we save this as add.r and run it via mpirun -np 3 Rscript add.r, we see:

function:
(rank=0)
function (a, b) a + b
output:
(rank=0)
[,1] [,2]
[1,] 33 39
[2,] 36 42

With three ranks, conceptually this is the same as calculating:

add=function(a, b) a+b
add(x, add(x+10, x+20))
## [,1] [,2]## [1,] 33 39## [2,] 36 42

As a more substantive example, we can build a matrix product reducer.

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
mult=function(a, b) a%*%bout= cop_allreduce(x, op=mult, commutative=FALSE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(mult)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

As before, most of the code is just boilerplate/printing. Really we only change the reducing function from the above. Note that we have to specify that the operation is not commutative.

If we save this as mult.r and run it via mpirun -np 3 Rscript mult.r, we see:

function:
(rank=0)
function (a, b) a %*% b
output:
(rank=0)
[,1] [,2]
[1,] 2197 2401
[2,] 3274 3578

With three ranks, conceptually this is the same as calculating:

x=matrix(1:4, 2)
mult=function(a, b) a%*%b
mult(x, mult(x+10, x+20))
## [,1] [,2]## [1,] 2197 2401## [2,] 3274 3578

You can find more examples in the inst/examples/ directory of the package source, or in examples/ of the installed package, located at system.file("examples", package="cop").

About

Custom operations for MPI reductions

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Add copy buttons to all
 blocks
(function() {
function addCopyButtons() {
document.querySelectorAll('pre code').forEach(function(codeBlock) {
if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;
codeBlock.parentElement.setAttribute('data-copy-added', 'true');
var btn = document.createElement('button');
btn.textContent = 'Copy';
btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';
btn.onmouseover = function() { this.style.opacity = '1'; };
btn.onmouseout = function() { this.style.opacity = '0.7'; };
btn.onclick = function() {
navigator.clipboard.writeText(codeBlock.textContent).then(function() {
btn.textContent = 'Copied!';
setTimeout(function() { btn.textContent = 'Copy'; }, 1500);
});
};
codeBlock.parentElement.style.position = 'relative';
codeBlock.parentElement.appendChild(btn);
});
}
addCopyButtons();
// Re-run on dynamic content
var observer = new MutationObserver(addCopyButtons);
observer.observe(document.body, { childList: true, subtree: true });
})();
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '
Skip to content

Repository files navigation

cop

Some custom reduction operations for data distributed over MPI.

Installation

The development version is maintained on GitHub. Because the package uses git submodules, you can not use any of the install_github() functions. Instead you can do this:

source("https://gist.githubusercontent.com/wrathematics/ccf6bf366279e099563e69e56b4fde59/raw/6daf038ca56f4f531f631f80a54d8d9aa70b4bbb/ighwsm.r")
ighwsm("RBigData/cop")

API

Dense, numeric matrix reductions:

MethodExplanation
cop_allreduce()Reduction that accepts a custom operation (R function). The function has some strong caveats; see ?cop::cop_allreduce for details.
cop_reduce()
qr_allreduce()Reduction where each process owns the R matrix of a QR decomposition, and the reduction is (conceptually) op = function(a, b) qr.R(qr(a, b)).
qr_reduce()

Sparse matrix reductions:

MethodExplanation
spadd_allreduce()Reduction where each process owns a sparse matrix (dgCMatrix from the Matrix package), and the reduction sums all of the matrices.
spadd_reduce()

The difference between the _reduce() and the _allreduce() variants is that with the former, only the process specified by the root argument receives the return.

The package also has some helper utilities:

MethodExplanation
mpi_cat()Helper cat() function.
mpi_print()Helper print() function.

These are similar to pbdMPI::comm.cat() and pbdMPI::comm.print(), although here printing is guaranteed to occur in rank order.

Examples

For the sake of example, we can build a matrix addition custom reducer:

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
add=function(a, b) a+bout= cop_allreduce(x, op=add, commutative=TRUE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(add)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

Most of this is just printing and boilerplate, but even so it's still pretty simple. If we save this as add.r and run it via mpirun -np 3 Rscript add.r, we see:

function:
(rank=0)
function (a, b) a + b
output:
(rank=0)
[,1] [,2]
[1,] 33 39
[2,] 36 42

With three ranks, conceptually this is the same as calculating:

add=function(a, b) a+b
add(x, add(x+10, x+20))
## [,1] [,2]## [1,] 33 39## [2,] 36 42

As a more substantive example, we can build a matrix product reducer.

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
mult=function(a, b) a%*%bout= cop_allreduce(x, op=mult, commutative=FALSE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(mult)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

As before, most of the code is just boilerplate/printing. Really we only change the reducing function from the above. Note that we have to specify that the operation is not commutative.

If we save this as mult.r and run it via mpirun -np 3 Rscript mult.r, we see:

function:
(rank=0)
function (a, b) a %*% b
output:
(rank=0)
[,1] [,2]
[1,] 2197 2401
[2,] 3274 3578

With three ranks, conceptually this is the same as calculating:

x=matrix(1:4, 2)
mult=function(a, b) a%*%b
mult(x, mult(x+10, x+20))
## [,1] [,2]## [1,] 2197 2401## [2,] 3274 3578

You can find more examples in the inst/examples/ directory of the package source, or in examples/ of the installed package, located at system.file("examples", package="cop").

About

Custom operations for MPI reductions

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Force GitHub README to respect dark mode (function() { var style = document.createElement('style'); style.textContent = ' .markdown-body { color-scheme: dark light; } .markdown-body pre { background: #161b22 !important; } .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; } .markdown-body table th, .markdown-body table td { border-color: #30363d !important; } .markdown-body img { background: #0d1117; } .markdown-body blockquote { border-left-color: #8b949e; } .markdown-body hr { border-color: #30363d; } '; document.head.appendChild(style); })(); } } catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Repository files navigation

cop

Some custom reduction operations for data distributed over MPI.

Installation

The development version is maintained on GitHub. Because the package uses git submodules, you can not use any of the install_github() functions. Instead you can do this:

source("https://gist.githubusercontent.com/wrathematics/ccf6bf366279e099563e69e56b4fde59/raw/6daf038ca56f4f531f631f80a54d8d9aa70b4bbb/ighwsm.r")
ighwsm("RBigData/cop")

API

Dense, numeric matrix reductions:

MethodExplanation
cop_allreduce()Reduction that accepts a custom operation (R function). The function has some strong caveats; see ?cop::cop_allreduce for details.
cop_reduce()
qr_allreduce()Reduction where each process owns the R matrix of a QR decomposition, and the reduction is (conceptually) op = function(a, b) qr.R(qr(a, b)).
qr_reduce()

Sparse matrix reductions:

MethodExplanation
spadd_allreduce()Reduction where each process owns a sparse matrix (dgCMatrix from the Matrix package), and the reduction sums all of the matrices.
spadd_reduce()

The difference between the _reduce() and the _allreduce() variants is that with the former, only the process specified by the root argument receives the return.

The package also has some helper utilities:

MethodExplanation
mpi_cat()Helper cat() function.
mpi_print()Helper print() function.

These are similar to pbdMPI::comm.cat() and pbdMPI::comm.print(), although here printing is guaranteed to occur in rank order.

Examples

For the sake of example, we can build a matrix addition custom reducer:

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
add=function(a, b) a+bout= cop_allreduce(x, op=add, commutative=TRUE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(add)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

Most of this is just printing and boilerplate, but even so it's still pretty simple. If we save this as add.r and run it via mpirun -np 3 Rscript add.r, we see:

function:
(rank=0)
function (a, b) a + b
output:
(rank=0)
[,1] [,2]
[1,] 33 39
[2,] 36 42

With three ranks, conceptually this is the same as calculating:

add=function(a, b) a+b
add(x, add(x+10, x+20))
## [,1] [,2]## [1,] 33 39## [2,] 36 42

As a more substantive example, we can build a matrix product reducer.

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
mult=function(a, b) a%*%bout= cop_allreduce(x, op=mult, commutative=FALSE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(mult)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

As before, most of the code is just boilerplate/printing. Really we only change the reducing function from the above. Note that we have to specify that the operation is not commutative.

If we save this as mult.r and run it via mpirun -np 3 Rscript mult.r, we see:

function:
(rank=0)
function (a, b) a %*% b
output:
(rank=0)
[,1] [,2]
[1,] 2197 2401
[2,] 3274 3578

With three ranks, conceptually this is the same as calculating:

x=matrix(1:4, 2)
mult=function(a, b) a%*%b
mult(x, mult(x+10, x+20))
## [,1] [,2]## [1,] 2197 2401## [2,] 3274 3578

You can find more examples in the inst/examples/ directory of the package source, or in examples/ of the installed package, located at system.file("examples", package="cop").

About

Custom operations for MPI reductions

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Highlight search terms from Google/DuckDuckGo/Bing referrer (function() { var ref = document.referrer; var terms = []; if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) { var url = new URL(ref); var q = url.searchParams.get('q') || url.searchParams.get('p'); if (q) { terms = q.split(/\s+/).filter(function(t) { return t.length > 2; }); } } if (terms.length === 0) return; var style = document.createElement('style'); style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }'; document.head.appendChild(style); function highlight(node) { if (node.nodeType === 3) { // text node var text = node.textContent; var found = false; terms.forEach(function(term) { var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\]\\]/g, '\\') + ')', 'gi'); if (regex.test(text)) { found = true; var frag = document.createDocumentFragment(); var parts = text.split(regex); parts.forEach(function(part, i) { if (i % 2 === 0) { frag.appendChild(document.createTextNode(part)); } else { var span = document.createElement('span'); span.className = 'userscript-highlight'; span.textContent = part; frag.appendChild(span); } }); node.parentNode.replaceChild(frag, node); } }); } else if (node.nodeType === 1 && node.childNodes) { // element var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT']; if (!skipTags.includes(node.tagName)) { Array.from(node.childNodes).forEach(highlight); } } } highlight(document.body); // Re-highlight on dynamic content var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1 || node.nodeType === 3) highlight(node); }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Repository files navigation

cop

Some custom reduction operations for data distributed over MPI.

Installation

The development version is maintained on GitHub. Because the package uses git submodules, you can not use any of the install_github() functions. Instead you can do this:

source("https://gist.githubusercontent.com/wrathematics/ccf6bf366279e099563e69e56b4fde59/raw/6daf038ca56f4f531f631f80a54d8d9aa70b4bbb/ighwsm.r")
ighwsm("RBigData/cop")

API

Dense, numeric matrix reductions:

MethodExplanation
cop_allreduce()Reduction that accepts a custom operation (R function). The function has some strong caveats; see ?cop::cop_allreduce for details.
cop_reduce()
qr_allreduce()Reduction where each process owns the R matrix of a QR decomposition, and the reduction is (conceptually) op = function(a, b) qr.R(qr(a, b)).
qr_reduce()

Sparse matrix reductions:

MethodExplanation
spadd_allreduce()Reduction where each process owns a sparse matrix (dgCMatrix from the Matrix package), and the reduction sums all of the matrices.
spadd_reduce()

The difference between the _reduce() and the _allreduce() variants is that with the former, only the process specified by the root argument receives the return.

The package also has some helper utilities:

MethodExplanation
mpi_cat()Helper cat() function.
mpi_print()Helper print() function.

These are similar to pbdMPI::comm.cat() and pbdMPI::comm.print(), although here printing is guaranteed to occur in rank order.

Examples

For the sake of example, we can build a matrix addition custom reducer:

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
add=function(a, b) a+bout= cop_allreduce(x, op=add, commutative=TRUE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(add)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

Most of this is just printing and boilerplate, but even so it's still pretty simple. If we save this as add.r and run it via mpirun -np 3 Rscript add.r, we see:

function:
(rank=0)
function (a, b) a + b
output:
(rank=0)
[,1] [,2]
[1,] 33 39
[2,] 36 42

With three ranks, conceptually this is the same as calculating:

add=function(a, b) a+b
add(x, add(x+10, x+20))
## [,1] [,2]## [1,] 33 39## [2,] 36 42

As a more substantive example, we can build a matrix product reducer.

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
mult=function(a, b) a%*%bout= cop_allreduce(x, op=mult, commutative=FALSE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(mult)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

As before, most of the code is just boilerplate/printing. Really we only change the reducing function from the above. Note that we have to specify that the operation is not commutative.

If we save this as mult.r and run it via mpirun -np 3 Rscript mult.r, we see:

function:
(rank=0)
function (a, b) a %*% b
output:
(rank=0)
[,1] [,2]
[1,] 2197 2401
[2,] 3274 3578

With three ranks, conceptually this is the same as calculating:

x=matrix(1:4, 2)
mult=function(a, b) a%*%b
mult(x, mult(x+10, x+20))
## [,1] [,2]## [1,] 2197 2401## [2,] 3274 3578

You can find more examples in the inst/examples/ directory of the package source, or in examples/ of the installed package, located at system.file("examples", package="cop").

About

Custom operations for MPI reductions

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Strip utm_, fbclid, gclid, etc. from all links on page (function() { var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content', 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid', 'ref', 'ref_src', 'source', 'medium', 'campaign']; function cleanUrl(url) { try { var u = new URL(url, window.location.origin); var changed = false; trackingParams.forEach(function(p) { if (u.searchParams.has(p)) { u.searchParams.delete(p); changed = true; } }); return changed ? u.toString() : url; } catch (e) { return url; } } function cleanLinks() { document.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } cleanLinks(); var observer = new MutationObserver(function(mutations) { mutations.forEach(function(m) { m.addedNodes.forEach(function(node) { if (node.nodeType === 1) { if (node.tagName === 'A') cleanLinks(); node.querySelectorAll('a[href]').forEach(function(a) { var clean = cleanUrl(a.href); if (clean !== a.href) a.href = clean; }); } }); }); }); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); } })(); (function(){ try { var __m = "youtube.com"; var __re = new RegExp('^' + "youtube\\.com" + '
Skip to content

Repository files navigation

cop

Some custom reduction operations for data distributed over MPI.

Installation

The development version is maintained on GitHub. Because the package uses git submodules, you can not use any of the install_github() functions. Instead you can do this:

source("https://gist.githubusercontent.com/wrathematics/ccf6bf366279e099563e69e56b4fde59/raw/6daf038ca56f4f531f631f80a54d8d9aa70b4bbb/ighwsm.r")
ighwsm("RBigData/cop")

API

Dense, numeric matrix reductions:

MethodExplanation
cop_allreduce()Reduction that accepts a custom operation (R function). The function has some strong caveats; see ?cop::cop_allreduce for details.
cop_reduce()
qr_allreduce()Reduction where each process owns the R matrix of a QR decomposition, and the reduction is (conceptually) op = function(a, b) qr.R(qr(a, b)).
qr_reduce()

Sparse matrix reductions:

MethodExplanation
spadd_allreduce()Reduction where each process owns a sparse matrix (dgCMatrix from the Matrix package), and the reduction sums all of the matrices.
spadd_reduce()

The difference between the _reduce() and the _allreduce() variants is that with the former, only the process specified by the root argument receives the return.

The package also has some helper utilities:

MethodExplanation
mpi_cat()Helper cat() function.
mpi_print()Helper print() function.

These are similar to pbdMPI::comm.cat() and pbdMPI::comm.print(), although here printing is guaranteed to occur in rank order.

Examples

For the sake of example, we can build a matrix addition custom reducer:

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
add=function(a, b) a+bout= cop_allreduce(x, op=add, commutative=TRUE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(add)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

Most of this is just printing and boilerplate, but even so it's still pretty simple. If we save this as add.r and run it via mpirun -np 3 Rscript add.r, we see:

function:
(rank=0)
function (a, b) a + b
output:
(rank=0)
[,1] [,2]
[1,] 33 39
[2,] 36 42

With three ranks, conceptually this is the same as calculating:

add=function(a, b) a+b
add(x, add(x+10, x+20))
## [,1] [,2]## [1,] 33 39## [2,] 36 42

As a more substantive example, we can build a matrix product reducer.

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
mult=function(a, b) a%*%bout= cop_allreduce(x, op=mult, commutative=FALSE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(mult)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

As before, most of the code is just boilerplate/printing. Really we only change the reducing function from the above. Note that we have to specify that the operation is not commutative.

If we save this as mult.r and run it via mpirun -np 3 Rscript mult.r, we see:

function:
(rank=0)
function (a, b) a %*% b
output:
(rank=0)
[,1] [,2]
[1,] 2197 2401
[2,] 3274 3578

With three ranks, conceptually this is the same as calculating:

x=matrix(1:4, 2)
mult=function(a, b) a%*%b
mult(x, mult(x+10, x+20))
## [,1] [,2]## [1,] 2197 2401## [2,] 3274 3578

You can find more examples in the inst/examples/ directory of the package source, or in examples/ of the installed package, located at system.file("examples", package="cop").

About

Custom operations for MPI reductions

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Auto-enable theater mode on YouTube (function() { function tryTheater() { var btn = document.querySelector('button[aria-label="Theater mode"], ytd-player #player button[title="Theater mode"]'); if (btn && !btn.classList.contains('activated')) { btn.click(); } } // Try immediately tryTheater(); // Try after navigation (SPA) var lastUrl = location.href; setInterval(function() { if (location.href !== lastUrl) { lastUrl = location.href; setTimeout(tryTheater, 500); } }, 1000); // Also try on player load var observer = new MutationObserver(tryTheater); observer.observe(document.body, { childList: true, subtree: true }); })(); } } catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Repository files navigation

cop

Some custom reduction operations for data distributed over MPI.

Installation

The development version is maintained on GitHub. Because the package uses git submodules, you can not use any of the install_github() functions. Instead you can do this:

source("https://gist.githubusercontent.com/wrathematics/ccf6bf366279e099563e69e56b4fde59/raw/6daf038ca56f4f531f631f80a54d8d9aa70b4bbb/ighwsm.r")
ighwsm("RBigData/cop")

API

Dense, numeric matrix reductions:

MethodExplanation
cop_allreduce()Reduction that accepts a custom operation (R function). The function has some strong caveats; see ?cop::cop_allreduce for details.
cop_reduce()
qr_allreduce()Reduction where each process owns the R matrix of a QR decomposition, and the reduction is (conceptually) op = function(a, b) qr.R(qr(a, b)).
qr_reduce()

Sparse matrix reductions:

MethodExplanation
spadd_allreduce()Reduction where each process owns a sparse matrix (dgCMatrix from the Matrix package), and the reduction sums all of the matrices.
spadd_reduce()

The difference between the _reduce() and the _allreduce() variants is that with the former, only the process specified by the root argument receives the return.

The package also has some helper utilities:

MethodExplanation
mpi_cat()Helper cat() function.
mpi_print()Helper print() function.

These are similar to pbdMPI::comm.cat() and pbdMPI::comm.print(), although here printing is guaranteed to occur in rank order.

Examples

For the sake of example, we can build a matrix addition custom reducer:

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
add=function(a, b) a+bout= cop_allreduce(x, op=add, commutative=TRUE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(add)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

Most of this is just printing and boilerplate, but even so it's still pretty simple. If we save this as add.r and run it via mpirun -np 3 Rscript add.r, we see:

function:
(rank=0)
function (a, b) a + b
output:
(rank=0)
[,1] [,2]
[1,] 33 39
[2,] 36 42

With three ranks, conceptually this is the same as calculating:

add=function(a, b) a+b
add(x, add(x+10, x+20))
## [,1] [,2]## [1,] 33 39## [2,] 36 42

As a more substantive example, we can build a matrix product reducer.

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
mult=function(a, b) a%*%bout= cop_allreduce(x, op=mult, commutative=FALSE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(mult)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

As before, most of the code is just boilerplate/printing. Really we only change the reducing function from the above. Note that we have to specify that the operation is not commutative.

If we save this as mult.r and run it via mpirun -np 3 Rscript mult.r, we see:

function:
(rank=0)
function (a, b) a %*% b
output:
(rank=0)
[,1] [,2]
[1,] 2197 2401
[2,] 3274 3578

With three ranks, conceptually this is the same as calculating:

x=matrix(1:4, 2)
mult=function(a, b) a%*%b
mult(x, mult(x+10, x+20))
## [,1] [,2]## [1,] 2197 2401## [2,] 3274 3578

You can find more examples in the inst/examples/ directory of the package source, or in examples/ of the installed package, located at system.file("examples", package="cop").

About

Custom operations for MPI reductions

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Remove or un-stick sticky/fixed headers that block content (function() { function unstick() { document.querySelectorAll('header, nav, [role="banner"], .header, .navbar, .sticky, .fixed-top, [style*="position: fixed"], [style*="position:sticky"]').forEach(function(el) { if (el.style.position === 'fixed' || el.style.position === 'sticky' || getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') { el.style.position = 'static'; el.style.top = 'auto'; el.style.zIndex = 'auto'; } }); } unstick(); var observer = new MutationObserver(unstick); observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] }); })(); } } catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); } })(); (function(){ try { var __m = "*"; var __re = new RegExp('^' + ".*" + '
Skip to content

Repository files navigation

cop

Some custom reduction operations for data distributed over MPI.

Installation

The development version is maintained on GitHub. Because the package uses git submodules, you can not use any of the install_github() functions. Instead you can do this:

source("https://gist.githubusercontent.com/wrathematics/ccf6bf366279e099563e69e56b4fde59/raw/6daf038ca56f4f531f631f80a54d8d9aa70b4bbb/ighwsm.r")
ighwsm("RBigData/cop")

API

Dense, numeric matrix reductions:

MethodExplanation
cop_allreduce()Reduction that accepts a custom operation (R function). The function has some strong caveats; see ?cop::cop_allreduce for details.
cop_reduce()
qr_allreduce()Reduction where each process owns the R matrix of a QR decomposition, and the reduction is (conceptually) op = function(a, b) qr.R(qr(a, b)).
qr_reduce()

Sparse matrix reductions:

MethodExplanation
spadd_allreduce()Reduction where each process owns a sparse matrix (dgCMatrix from the Matrix package), and the reduction sums all of the matrices.
spadd_reduce()

The difference between the _reduce() and the _allreduce() variants is that with the former, only the process specified by the root argument receives the return.

The package also has some helper utilities:

MethodExplanation
mpi_cat()Helper cat() function.
mpi_print()Helper print() function.

These are similar to pbdMPI::comm.cat() and pbdMPI::comm.print(), although here printing is guaranteed to occur in rank order.

Examples

For the sake of example, we can build a matrix addition custom reducer:

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
add=function(a, b) a+bout= cop_allreduce(x, op=add, commutative=TRUE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(add)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

Most of this is just printing and boilerplate, but even so it's still pretty simple. If we save this as add.r and run it via mpirun -np 3 Rscript add.r, we see:

function:
(rank=0)
function (a, b) a + b
output:
(rank=0)
[,1] [,2]
[1,] 33 39
[2,] 36 42

With three ranks, conceptually this is the same as calculating:

add=function(a, b) a+b
add(x, add(x+10, x+20))
## [,1] [,2]## [1,] 33 39## [2,] 36 42

As a more substantive example, we can build a matrix product reducer.

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
mult=function(a, b) a%*%bout= cop_allreduce(x, op=mult, commutative=FALSE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(mult)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

As before, most of the code is just boilerplate/printing. Really we only change the reducing function from the above. Note that we have to specify that the operation is not commutative.

If we save this as mult.r and run it via mpirun -np 3 Rscript mult.r, we see:

function:
(rank=0)
function (a, b) a %*% b
output:
(rank=0)
[,1] [,2]
[1,] 2197 2401
[2,] 3274 3578

With three ranks, conceptually this is the same as calculating:

x=matrix(1:4, 2)
mult=function(a, b) a%*%b
mult(x, mult(x+10, x+20))
## [,1] [,2]## [1,] 2197 2401## [2,] 3274 3578

You can find more examples in the inst/examples/ directory of the package source, or in examples/ of the installed package, located at system.file("examples", package="cop").

About

Custom operations for MPI reductions

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { // Universal Dark Mode - works on any site (function() { var enabled = true; function applyDarkMode() { if (!enabled) return; // Create style element if it doesn't exist var style = document.getElementById('universal-dark-mode-style'); if (!style) { style = document.createElement('style'); style.id = 'universal-dark-mode-style'; document.head.appendChild(style); } // Dark mode CSS - inverts colors but preserves images/video style.textContent = ' /* Invert everything except media */ html { filter: invert(1) hue-rotate(180deg) !important; background: #1a1a2e !important; } /* Restore images, videos, iframes, canvas */ img, video, iframe, canvas, svg, picture, [style*="background-image"] { filter: invert(1) hue-rotate(180deg) !important; } /* Preserve specific elements that should not be inverted */ .no-dark-mode, .no-dark-mode *, [data-theme="light"], [data-theme="light"], .ace_editor, .ace_editor *, .CodeMirror, .CodeMirror *, .monaco-editor, .monaco-editor *, .markdown-body pre, .markdown-body pre *, .highlight, .highlight *, pre code, pre code * { filter: none !important; } /* Fix common UI elements */ .modal, .popup, .dropdown-menu, .tooltip, .popover { filter: invert(1) hue-rotate(180deg) !important; background: #2d2d44 !important; border-color: #444 !important; } /* Scrollbars */ ::-webkit-scrollbar { background: #1a1a2e !important; } ::-webkit-scrollbar-thumb { background: #444 !important; } ::-webkit-scrollbar-thumb:hover { background: #555 !important; } /* Selection */ ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; } ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; } '; } function removeDarkMode() { var style = document.getElementById('universal-dark-mode-style'); if (style) style.remove(); } // Toggle with Alt+Shift+D document.addEventListener('keydown', function(e) { if (e.altKey && e.shiftKey && e.key === 'D') { e.preventDefault(); enabled = !enabled; if (enabled) { applyDarkMode(); console.log('[Universal Dark Mode] Enabled'); } else { removeDarkMode(); console.log('[Universal Dark Mode] Disabled'); } } }); // Apply on load applyDarkMode(); // Re-apply on dynamic content var observer = new MutationObserver(function(mutations) { if (enabled && !document.getElementById('universal-dark-mode-style')) { applyDarkMode(); } }); observer.observe(document.head, { childList: true }); console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle'); })(); } } catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); } })(); })();
Skip to content

Repository files navigation

cop

Some custom reduction operations for data distributed over MPI.

Installation

The development version is maintained on GitHub. Because the package uses git submodules, you can not use any of the install_github() functions. Instead you can do this:

source("https://gist.githubusercontent.com/wrathematics/ccf6bf366279e099563e69e56b4fde59/raw/6daf038ca56f4f531f631f80a54d8d9aa70b4bbb/ighwsm.r")
ighwsm("RBigData/cop")

API

Dense, numeric matrix reductions:

MethodExplanation
cop_allreduce()Reduction that accepts a custom operation (R function). The function has some strong caveats; see ?cop::cop_allreduce for details.
cop_reduce()
qr_allreduce()Reduction where each process owns the R matrix of a QR decomposition, and the reduction is (conceptually) op = function(a, b) qr.R(qr(a, b)).
qr_reduce()

Sparse matrix reductions:

MethodExplanation
spadd_allreduce()Reduction where each process owns a sparse matrix (dgCMatrix from the Matrix package), and the reduction sums all of the matrices.
spadd_reduce()

The difference between the _reduce() and the _allreduce() variants is that with the former, only the process specified by the root argument receives the return.

The package also has some helper utilities:

MethodExplanation
mpi_cat()Helper cat() function.
mpi_print()Helper print() function.

These are similar to pbdMPI::comm.cat() and pbdMPI::comm.print(), although here printing is guaranteed to occur in rank order.

Examples

For the sake of example, we can build a matrix addition custom reducer:

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
add=function(a, b) a+bout= cop_allreduce(x, op=add, commutative=TRUE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(add)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

Most of this is just printing and boilerplate, but even so it's still pretty simple. If we save this as add.r and run it via mpirun -np 3 Rscript add.r, we see:

function:
(rank=0)
function (a, b) a + b
output:
(rank=0)
[,1] [,2]
[1,] 33 39
[2,] 36 42

With three ranks, conceptually this is the same as calculating:

add=function(a, b) a+b
add(x, add(x+10, x+20))
## [,1] [,2]## [1,] 33 39## [2,] 36 42

As a more substantive example, we can build a matrix product reducer.

suppressMessages(library(cop))
x=matrix(1:4, 2) +10*comm.rank()
mult=function(a, b) a%*%bout= cop_allreduce(x, op=mult, commutative=FALSE)
mpi_cat("\nfunction:\n", quiet=TRUE)
mpi_print(mult)
mpi_cat("\noutput:\n", quiet=TRUE)
mpi_print(out)
finalize()

As before, most of the code is just boilerplate/printing. Really we only change the reducing function from the above. Note that we have to specify that the operation is not commutative.

If we save this as mult.r and run it via mpirun -np 3 Rscript mult.r, we see:

function:
(rank=0)
function (a, b) a %*% b
output:
(rank=0)
[,1] [,2]
[1,] 2197 2401
[2,] 3274 3578

With three ranks, conceptually this is the same as calculating:

x=matrix(1:4, 2)
mult=function(a, b) a%*%b
mult(x, mult(x+10, x+20))
## [,1] [,2]## [1,] 2197 2401## [2,] 3274 3578

You can find more examples in the inst/examples/ directory of the package source, or in examples/ of the installed package, located at system.file("examples", package="cop").

About

Custom operations for MPI reductions

Topics

Resources

Stars

2 stars

Watchers

1 watching

Forks

Releases

Packages

Contributors

Languages